Vulnerability-Lookup

CNVD-2018-16938

Vulnerability from cnvd - Published: 2018-08-30

Title

All For One信息泄露漏洞

Description

All For One是一款基于以太坊的赌博游戏。 All For One的智能合约实现中的‘maxRandom’函数存在信息泄露漏洞，该漏洞源于程序使用公开可读取的变量来生成任意值。攻击者可利用该漏洞推测生成的任意数，进而获得奖励。

Severity

中

Formal description

厂商尚未提供漏洞修复方案，请关注厂商主页更新： https://all-for-one.club/

Reference

https://medium.com/@jonghyk.song/to-be-a-winner-of-ethereum-gambling-game-all-for-one-by-breaking-prng-1ab011163d40

Impacted products

Name
All For One All For One

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2018-12056"
    }
  },
  "description": "All For One\u662f\u4e00\u6b3e\u57fa\u4e8e\u4ee5\u592a\u574a\u7684\u8d4c\u535a\u6e38\u620f\u3002\r\n\r\nAll For One\u7684\u667a\u80fd\u5408\u7ea6\u5b9e\u73b0\u4e2d\u7684\u2018maxRandom\u2019\u51fd\u6570\u5b58\u5728\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u4f7f\u7528\u516c\u5f00\u53ef\u8bfb\u53d6\u7684\u53d8\u91cf\u6765\u751f\u6210\u4efb\u610f\u503c\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u63a8\u6d4b\u751f\u6210\u7684\u4efb\u610f\u6570\uff0c\u8fdb\u800c\u83b7\u5f97\u5956\u52b1\u3002",
  "discovererName": "unknown",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttps://all-for-one.club/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2018-16938",
  "openTime": "2018-08-30",
  "products": {
    "product": "All For One All For One"
  },
  "referenceLink": "https://medium.com/@jonghyk.song/to-be-a-winner-of-ethereum-gambling-game-all-for-one-by-breaking-prng-1ab011163d40",
  "serverity": "\u4e2d",
  "submitTime": "2018-08-17",
  "title": "All For One\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e"
}

CVE-2018-12056 (GCVE-0-2018-12056)

Vulnerability from cvelistv5 – Published: 2018-08-15 17:00 – Updated: 2024-08-05 08:24

Summary

The maxRandom function of a smart contract implementation for All For One, an Ethereum gambling game, generates a random value with publicly readable variables because the _seed value can be retrieved with a getStorageAt call. Therefore, it allows attackers to always win and get rewards.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

2 references

URL	Tags
https://medium.com/%40jonghyk.song/to-be-a-winner…	x_refsource_MISC
https://lists.apache.org/thread.html/a62aa2706105…	mailing-listx_refsource_MLIST

Date Public

2018-08-09 00:00

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.